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(More customer reviews)Often in clinical trials particularly oncology trials time-to-event are the endpoints of primary interest. The endpoint could be time of death, time to remittance, time to recurrence or something else. In the recent RE-LY trial which was a stroke prevention trial the dual primary endpoints were time-to-an-occurrence of stroke and time-to-a-major bleeding episode. It seems almost always the case that the study will involved estimating these parameters based on data the include a lot of right-censoring. So the methods of survival or relaibility analysis come to play an imprtant role. Usually if the events are rare the sample size requirement will be large because power of the test of differences between two groups is dictated by the number of events which then requires large sample size s to achieve the requisite number of events. The RE-LY trial was a noninferiority trial with three equal size treatment arms and rare event occurrences. So thid trial required approximately 18000 subjects with 600 in each group. Such trials are long, difficult to administer and very expensive. So often the time-to-event endpoint is replaced by a surrogate endpoint.
Karl Peace has edited and contributed to a very timely volume on the design and analysis of time-to-event endpoints in clinical trials. This book can serve as a text or a reference for biostatisticians and particularly those involved in clinical trials, especially oncology trials. A number of authors with a lot of experience with such trials were chosen to contribute to this volume. The first 6 chapters are introductory and mostly overviews of a particular methodology. Chapter 1 by Peace,is a general overview of the topic and an introdcution to what is included in the remaining chapters. Chapter 2 by Sill and Rubinstein introduces how time-to-event endpoint trials are designed and monitored. Chapter 3 is an overview of parametric models for time-to-event distrbution by Peace and Tsai. Chapter 4 does the same for semiparametric methods (the Cox proportional hazard model and its extensions) Chapter 5 is an overview of methods to handle categorical time-to-event data. Chapters 6 and 9 cover overviews of Bayesian methods applied to time-to-event data and graphical approaches respectively. These chapters read like they are part of an introductory text and they have large reference lists for very pertinent and up-to-date articles and books. The other chapters are mostly specialized topics such as chapter 8 by Bhore and Huque on the estimation and and testing of a change in the hazard rate in the survival curve.
I particularly like the book because it provides a refresher course that also includes new approaches or old ones that I am not so familiar with. It is a very important and authoritative text that any statistician doing time-to-event trials can rely on.
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Using time-to-event analysis methodology requires careful definition of the event, censored observation, provision of adequate follow-up, number of events, and independence or "noninformativeness" of the censoring mechanisms relative to the event. Design and Analysis of Clinical Trials with Time-to-Event Endpoints provides a thorough presentation of the design, monitoring, analysis, and interpretation of clinical trials in which time-to-event is of critical interest.After reviewing time-to-event endpoint methodology, clinical trial issues, and the design and monitoring of clinical trials, the book focuses on inferential analysis methods, including parametric, semiparametric, categorical, and Bayesian methods; an alternative to the Cox model for small samples; and estimation and testing for change in hazard. It then presents descriptive and graphical methods useful in the analysis of time-to-event endpoints. The next several chapters explore a variety of clinical trials, from analgesic, antibiotic, and antiviral trials to cardiovascular and cancer prevention, prostate cancer, astrocytoma brain tumor, and chronic myelogonous leukemia trials. The book then covers areas of drug development, medical practice, and safety assessment. It concludes with the design and analysis of clinical trials of animals required by the FDA for new drug applications.Drawing on the expert contributors' experiences working in biomedical research and clinical drug development, this comprehensive resource covers an array of time-to-event methods and explores an assortment of real-world applications.
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